PhD Position in Medical Imaging AI at the University of Zurich and AWS: Apply for a PhD in 3D Medical Imaging, AI and Computer Vision

The Department of Quantitative Biomedicine at the University of Zurich (UZH) is inviting applications for a PhD position focused on Medical Imaging AI, offering an opportunity for researchers interested in artificial intelligence, computer vision, medical image computing and clinically relevant machine learning research.

The PhD position is jointly affiliated with the University of Zurich (UZH) and the University Hospital Zurich (USZ), with the possibility of an additional affiliation with the ETH AI Center for an appropriate candidate. The research will also be conducted in active collaboration with the AWS for Healthcare team, giving the successful candidate an opportunity to work at the intersection of advanced AI research, medical imaging and real-world healthcare applications.

The position is particularly relevant to candidates with academic backgrounds in Computer Science, Physics, Mathematics, Engineering or closely related disciplines who have a strong interest in medical applications of artificial intelligence and are motivated to develop and scale AI algorithms through the AWS ecosystem.

Host Institutions and Research Environment

The position is hosted by the Department of Quantitative Biomedicine at the University of Zurich and is jointly affiliated with the University Hospital Zurich. The research environment also has strong connections to ETH Zurich, with the possibility for a suitable candidate to affiliate with the ETH AI Center.

A distinctive feature of this opportunity is the collaboration with the AWS for Healthcare team. Rather than focusing solely on theoretical or laboratory-based research, the PhD will combine methodological research with direct clinical relevance and opportunities to translate research outcomes into practical algorithms and applications.

This makes the position particularly attractive for researchers who want to develop expertise not only in artificial intelligence and medical imaging but also in the transition of research innovations into real-world healthcare technology.

Research Areas for the PhD

The PhD position focuses on several interconnected areas of medical imaging artificial intelligence. Applicants should be prepared to engage with advanced computational methods and their application to medical data.

1. Vision-Language Modeling for 3D Medical Imaging

One of the central research directions is vision-language modeling (VLM) for three-dimensional medical imaging.

Vision-language models seek to connect visual information with language-based information. In the context of medical imaging, this can involve developing AI systems capable of understanding complex medical images and relating their visual content to textual descriptions, clinical findings or other forms of medical knowledge.

The position specifically highlights work involving 3D medical imaging, including research associated with CT imaging and the CT-RATE dataset.

This research area has significant potential applications in medical image interpretation, automated reporting, clinical decision support and multimodal healthcare AI.

2. Image Segmentation

Another major research focus is medical image segmentation.

Image segmentation involves identifying and delineating specific structures, organs, tissues, lesions or other clinically relevant regions within medical images.

For a PhD researcher, this area may involve developing machine learning and deep learning approaches that can accurately identify structures within complex medical images and improve the reliability of automated medical image analysis.

The position references research including CADS and vesselFM as part of its segmentation and visual grounding focus.

3. Visual Grounding

The PhD will also address visual grounding, an area concerned with linking language or semantic descriptions to specific regions or objects within visual data.

In medical imaging, visual grounding can contribute to AI systems that do more than simply classify an image. Such systems can potentially identify and associate particular anatomical structures or abnormalities with corresponding clinical concepts or descriptions.

This creates an important connection between computer vision, natural language processing and medical image understanding.

4. Clinical Validation

The research will not stop at developing AI models.

A major component of the position is clinical validation, meaning that developed approaches will need to be assessed for their usefulness and performance in medically relevant settings.

This clinical orientation is one of the defining features of the opportunity. The research will combine methods-driven artificial intelligence research with direct clinical relevance through the UZH and University Hospital Zurich environment.

5. Benchmarking and Public Challenges

The PhD researcher will also have the opportunity to participate in public benchmarking initiatives.

Benchmarking allows researchers to compare AI systems using common datasets, evaluation procedures and performance measures. It can help determine whether a proposed method provides meaningful improvements over existing approaches.

The position specifically references initiatives including VLM3D and BRATS.

Participation in such initiatives can also help researchers build an international research profile and contribute to the broader medical AI research community.

What the PhD Position Offers

The University of Zurich’s opportunity provides an interdisciplinary research environment combining academic research, healthcare and industry collaboration.

According to the official position announcement, successful candidates can benefit from several important opportunities.

1. Research at the Intersection of AI and Medicine

The position combines advanced computational and AI methods with direct clinical applications.

This means the PhD researcher will have the opportunity to investigate sophisticated artificial intelligence methods while considering how those methods can address real healthcare and medical imaging challenges.

2. Affiliation with Leading Swiss Research Institutions

The position is based at UZH and USZ and has strong ties to ETH Zurich.

For an appropriate candidate, there is also the possibility of affiliation with the ETH AI Center, providing an additional connection to Switzerland’s highly developed artificial intelligence research ecosystem.

3. Collaboration with AWS for Healthcare

The successful researcher will work closely with the AWS for Healthcare team and participate in joint activities.

This provides exposure to an industry environment alongside academic and clinical research.

For candidates interested in developing AI systems that can eventually operate at scale, this industry connection may be particularly valuable.

4. Translating Research into Real-World Applications

The PhD offers an opportunity to contribute to the translation of research into real-world algorithms and applications within the AWS ecosystem.

This practical orientation can help bridge the gap between academic research and technology implementation.

5. Access to Clinical Collaborators

The position provides access to clinical collaborators, enabling researchers to work in an environment where medical expertise can inform the development and evaluation of AI systems.

This is especially important in medical AI because successful models need to address real clinical requirements rather than simply perform well on technical datasets.

6. Curated Medical Datasets

The researcher will have access to curated datasets relevant to medical imaging research.

High-quality datasets are essential for developing, training and evaluating machine learning systems, particularly in specialized areas such as 3D medical imaging.

7. Modern Computing Infrastructure

The position also provides access to modern computational infrastructure, including AWS cloud computing resources.

This can be important for computationally intensive research involving large medical imaging datasets and advanced AI models.

Who Is Eligible to Apply?

The position is aimed at candidates with a strong technical and research background relevant to artificial intelligence and medical image computing.

The official announcement identifies the following candidate profile.

Academic Background

Applicants should have a degree in:

Computer Science
Physics
Mathematics
Engineering
Or a closely related field

The position is therefore particularly suited to graduates whose academic training provides a strong foundation in quantitative, computational or technical research.

Interest in the Medical Domain

An intrinsic interest in the medical domain is required.

The university indicates that this interest should ideally be demonstrated through previous academic work, such as a related Master’s thesis or research project.

Candidates should therefore be able to demonstrate more than a general interest in artificial intelligence. A convincing application should explain why the applicant is interested in applying AI and computational methods to healthcare and medical imaging.

Interest in AWS and Scalable AI

Applicants are also expected to have a genuine interest in working with AWS to establish and scale algorithms and applications through the AWS ecosystem.

Candidates should therefore consider highlighting any relevant experience or interest in areas such as:

Machine learning
Deep learning
Computer vision
Medical image analysis
Cloud computing
Artificial intelligence
Data science
Algorithm development
Research software
Scalable computing systems

Who Can Apply?

The official announcement does not specify a particular nationality, race, ethnicity or continent restriction. The listed eligibility requirements focus primarily on academic background, interest in medical research and motivation to work with AWS.

Therefore, based on the published criteria, the opportunity can be considered open to qualified applicants internationally rather than being restricted to applicants from a particular country or continent.

Applicants from Africa, Asia, Europe, North America, South America, Oceania and other regions may be considered provided they satisfy the academic and research requirements. The announcement does not identify a nationality or racial restriction.

However, applicants should rely on the official university announcement for any additional admission, immigration, employment or doctoral-registration requirements that may apply during the application or enrollment process.

Application Requirements

Interested candidates are required to submit three key documents.

1. Curriculum Vitae

Applicants should submit an updated CV highlighting their academic background, research experience, technical skills, projects, publications and other experience relevant to medical AI and computational research.

Where applicable, candidates should emphasize experience with:

Artificial intelligence
Machine learning
Deep learning
Computer vision
Medical imaging
Image segmentation
Natural language processing
Vision-language models
Data science
Programming
Cloud computing
Research projects
Scientific publications

2. Transcript of Records

Applicants must provide their transcript of records.

The transcript helps demonstrate the candidate’s academic preparation and performance.

Candidates should ensure that the submitted transcript is clear and readable and adequately reflects their relevant academic coursework.

3. Brief Statement of Motivation

Applicants must also submit a brief statement of motivation.

This document should explain why the candidate is interested in the PhD position and why their academic and research background makes them suitable for the project.

A strong motivation statement should connect three major elements:

Your academic and technical background
Your interest in medical imaging and AI
Your motivation to work with UZH, USZ and AWS

Rather than simply stating that you are interested in artificial intelligence, the statement should demonstrate how your previous studies, research projects or technical experience have prepared you for the proposed research area.

How to Apply

Applications should be sent directly by email to:

bjoern.menze@uzh.ch

Applicants should include:

CV
Transcript of records
Brief statement of motivation

The email subject line should clearly state:

“PhD Position UZH-AWS”

APPLY HERE

Application Deadline

The official UZH webpage currently states the deadline as 31 September 2026.

However, September has only 30 days, meaning 31 September is not a valid calendar date. In addition, a recent post by the research group supervisor, Prof. Bjoern Menze, has publicly indicated 30 September 2026 as the deadline.

Applicants should therefore treat 30 September 2026 as the likely intended deadline and, importantly, confirm the deadline directly with UZH before submitting.

Because the official university webpage itself contains the apparent date error, applicants should avoid waiting until the final day and should submit their applications as early as possible.

How to Make Your Application Competitive

This is a specialized PhD opportunity, so applicants should carefully demonstrate their suitability rather than submitting a generic doctoral application.

1. Demonstrate Technical Preparation

Show evidence of your ability to work with quantitative and computational research.

Relevant coursework, research projects, programming experience and technical projects can strengthen your application.

2. Connect Your Experience to Medical Imaging

If you have previously worked on medical imaging, biomedical engineering, healthcare AI, computer vision or related research, make this connection explicit.

If your background is primarily in computer science or another technical discipline, explain clearly how you intend to apply your existing expertise to medical research.

3. Explain Your Interest in AI for Healthcare

The project is not simply an AI research position. It is specifically concerned with medical imaging AI.

Your motivation statement should therefore explain why you want to work on healthcare applications and what makes this research area particularly meaningful to you.

4. Highlight Research Experience

Where applicable, mention:

Master’s research
Research assistant positions
Academic publications
Conference presentations
Machine learning projects
Computer vision projects
Medical research projects
Open-source contributions
Relevant software or technical projects

5. Demonstrate Interest in Industry Collaboration

Because the PhD involves close collaboration with AWS for Healthcare, applicants should demonstrate that they are interested in translating research into practical applications.

Experience working with industry, cloud technologies, applied AI projects or scalable computational systems can therefore be useful to highlight.

6. Explain Your Long-Term Research Goals

A strong application should demonstrate how the PhD fits into your broader research and professional ambitions.

For example, candidates may explain their interest in developing AI systems that can improve medical image interpretation, clinical decision-making, healthcare efficiency or biomedical research.

Why This PhD Opportunity Stands Out

The UZH-AWS PhD position brings together four important components that are increasingly influential in modern healthcare research:

Artificial Intelligence + Medical Imaging + Clinical Research + Cloud Technology

The combination provides a distinctive research environment.

Instead of developing AI models in isolation, researchers will have opportunities to work with clinical collaborators, medical datasets and industry partners while investigating advanced approaches such as vision-language modeling, segmentation and visual grounding.

The position also provides exposure to benchmarking and clinical validation, allowing research outcomes to be evaluated against established standards and potentially translated into practical healthcare applications.

Visit HERE for more information about the PhD Position in Medical Imaging AI at the University of Zurich and AWS.

Key Details at a Glance

Opportunity: PhD Position in Medical Imaging AI
Host: University of Zurich
Clinical affiliation: University Hospital Zurich
Potential additional affiliation: ETH AI Center
Industry collaborator: AWS for Healthcare
Location: Zurich, Switzerland
Research area: Medical image computing and artificial intelligence
Major research topics: 3D vision-language modeling, image segmentation, visual grounding, clinical validation and benchmarking
Eligible academic backgrounds: Computer Science, Physics, Mathematics, Engineering and closely related disciplines
Medical interest: Required
AWS interest: Required
Application documents: CV, transcript of records and brief motivation statement
Application method: Email
Application email: bjoern.menze@uzh.ch
Required subject line: “PhD Position UZH-AWS”
Deadline stated on official page: 31 September 2026, which is an invalid calendar date
Likely intended deadline: 30 September 2026, based on the research group’s public announcement
Nationality restriction: None stated in the published eligibility criteria
Opportunity category: PhD Position / Doctoral Research Opportunity

Conclusion

The PhD Position UZH-AWS in Medical Imaging AI offers an opportunity for technically trained researchers to pursue doctoral research at the intersection of artificial intelligence, medical imaging and healthcare.

With research spanning 3D vision-language modeling, image segmentation, visual grounding, clinical validation and benchmarking, the project is designed for candidates who want to tackle challenging problems in medical image computing while maintaining a strong connection to real-world clinical applications.

The collaboration between the University of Zurich, University Hospital Zurich and AWS for Healthcare, together with potential links to the ETH AI Center, creates a multidisciplinary environment in which doctoral research can connect academic innovation with practical healthcare technology.

Applicants with backgrounds in Computer Science, Physics, Mathematics, Engineering or related disciplines should carefully assess their academic preparation, research interests and motivation for working in medical AI before applying.